#llm Development Tutorials & Tips | Roast Dev

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Building a CLI for Multi-Agent Tree-of-Thought: From Idea to Execution - Part 1

What if LLMs had opinions and argued in threads? What happens when we give LLMs not just memory and tools, but also autonomy, voices, perspectives, and structure? I built a simple CLI tool, a tiny ex...

04.05.2025 0 Read More

Growing the Tree: Multi-Agent LLMs Meet RAG, Vector Search, and Goal-Oriented Thinking - Part 2

Simulating Better Decision-Making in Insurance and Care Management Through RAGIn the Part 1 post, I walked through how I built a CLI that runs multi-agent conversations in a social media (Reddit-inspi...

04.05.2025 0 Read More

Asking Copilot About Writing a New Programming Language

Jesse: “Yo Copilot, if you were going to write a soundly typed language with managed effects that compiles to JavaScript, which language would you choose to write the compiler in?”Copilot: :: Reco...

04.05.2025 0 Read More

Build a knowledge graph from documents using Docling

First experience of building a knowledge graph from a document using Docling! Introduction and motivation Knowledge graphs are powerful tools for representing information in a structured way. ...

23.04.2025 0 Read More

Multi-Agent LLM Systems in 2025

Large language models like ChatGPT have become commonplace tools, helping me write emails as well as code. Other times, though, I found that one LLM wasn't sufficient to manage complex, multistep ta...

24.04.2025 0 Read More

Elevating LLM Evaluation with DeepEval with Native AWS Bedrock Support

Elevating LLM Evaluation with DeepEval: Now with Native AWS Bedrock Support As Large Language Models (LLMs) move from research labs to production environments, robust evaluation becomes criti...

24.04.2025 0 Read More

Keeping AI Pair Programmers On Track: Minimizing Context Drift in LLM-Assisted Workflows

Keeping AI Pair Programmers On Track: Minimizing Context Drift in LLM-Assisted Workflows In this post, we'll explore how to effectively manage context drift in AI coding assistants by using t...

24.04.2025 0 Read More

Turn Your OpenAPI Specs Into Agentic Tools—Instantly

What if your internal APIs could talk to AI agents without manual integration, schema rewrites, or hallucination-prone trial and error?Now they can.We’re excited to introduce a powerful new feature ...

25.04.2025 0 Read More

What the Heck Are Hybrid Knowledge Bases? (And Why They Matter for LLM Apps)

If you're building with LLMs and trying to give your agents or copilots real context, you've probably used a vector database.They're great for unstructured data — PDFs, HTML, markdown, text blobs. B...

25.04.2025 0 Read More

Build a Local ChatGPT-like App with Blazor and MAIN.NET – Part 3: Chatting with Your PDF Files.

Welcome back to the series! 👋 In Part 2, we added chat history support, allowing our app to maintain conversation context like a real assistant.Today, we’re taking another big step forward — en...

25.04.2025 0 Read More

Building a CLI for Multi-Agent Tree-of-Thought: From Idea to Execution - Part 1

Growing the Tree: Multi-Agent LLMs Meet RAG, Vector Search, and Goal-Oriented Thinking - Part 2

Asking Copilot About Writing a New Programming Language

Build a knowledge graph from documents using Docling

Multi-Agent LLM Systems in 2025

Elevating LLM Evaluation with DeepEval with Native AWS Bedrock Support

Keeping AI Pair Programmers On Track: Minimizing Context Drift in LLM-Assisted Workflows

Turn Your OpenAPI Specs Into Agentic Tools—Instantly

What the Heck Are Hybrid Knowledge Bases? (And Why They Matter for LLM Apps)

Build a Local ChatGPT-like App with Blazor and MAIN.NET – Part 3: Chatting with Your PDF Files.

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